{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6804c8bc-03c5-43a1-b00e-862177928abd",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#########################################################################\n",
    "# Jupyter notebook for analysis of alcaloid similarities;               #\n",
    "# Created by Elena Maria Beck and Michael Edmund Beck, November 2021    #\n",
    "# supplement to \"A conserved hymenopteran-specific family of cytochrome #\n",
    "# P450s protect bee polinators from toxic nectar alkaloids\"             #\n",
    "#########################################################################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5866fc78-8a91-4db7-9a21-b4a2b30d4329",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from rdkit import Chem\n",
    "from rdkit.Chem import AllChem       # enable Morgan fingerprints\n",
    "from rdkit.Chem import Draw          # enable drawing molecules\n",
    "from rdkit import DataStructs        # enable similarity calculation\n",
    "from matplotlib import pyplot as plt # histogram plot\n",
    "from rdkit.Chem import MACCSkeys     # gues what ... \n",
    "from itertools import *              # iterators and stuff\n",
    "import seaborn as sns                # enable clustering and heatmap\n",
    "import numpy as np                   # matrix and array manipulations\n",
    "import pandas as pd                  # data frames\n",
    "import matplotlib.pyplot as plt\n",
    "import networkx as nx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f0672c77-1224-4507-aceb-2c1357b72e42",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# create data set, manually, from SMILES codes\n",
    "data = np.array([\n",
    "    [\"C=1C=C([C@]2(N(CCC2)C)[H])C=NC1\",\"(S)-Nicotine\"],\n",
    "    [\"C1CCC(NC1)c1cccnc1\", \"Anabasine\"],\n",
    "    [\"CN1[C@H]2CC[C@@H]1C[C@@H](C2)OC(=O)C(CO)c1ccccc1\",\"Atropine\"],\n",
    "    [\"O=c1cccc2[C@H]3CNC[C@H](C3)Cn12\", \"Cytisine\"],\n",
    "    [\"C\\C=C(\\C)C(=O)O[C@@H]1CCN2CC=C(COC(=O)[C@@](O)([C@H](C)O)C(C)(C)O)[C@H]12\", \"Echimidine\"],\n",
    "    [\"CN1[C@H]2C[C@@H](C[C@@H]1[C@H]1O[C@@H]21)OC(=O)[C@H](CO)c1ccccc1\",\"Scopolamine\"],\n",
    "    [\"CN1C=NC2=C1C(=O)N(C(=O)N2C)C\",\"Caffeine\"],\n",
    "    [\"O=C1C=Cc2ccccc2O1\", \"Coumarin\"]]\n",
    "    )\n",
    "smiles = [a[0] for a in data]\n",
    "molNames =[a[1] for a in data]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "26855ea8-1e23-48bf-a19f-2a3f20b3e3b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# create molecule objects from smiles\n",
    "mols = pd.DataFrame([Chem.MolFromSmiles(x) for x in smiles],index=molNames)\n",
    "molImages = pd.DataFrame([Draw.MolToImage(m) for m in mols[0]],index=mols.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5f2b7520-c54c-44d6-9220-4182419e4d47",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Have a look at what we've got\n",
    "Draw.MolsToGridImage(mols[0], molsPerRow=4, subImgSize=(200,200), legends=[str(x) for x in mols.index] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9c5791d9-4764-4721-a290-9361ef823ec8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# calculate fingerprints\n",
    "Morgan2FP = [AllChem.GetMorganFingerprint(m,2,useFeatures=True) for m in mols[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a693bcf7-4ca2-4105-9876-fe864f1ef021",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>(S)-Nicotine</th>\n",
       "      <th>Anabasine</th>\n",
       "      <th>Atropine</th>\n",
       "      <th>Cytisine</th>\n",
       "      <th>Echimidine</th>\n",
       "      <th>Scopolamine</th>\n",
       "      <th>Caffeine</th>\n",
       "      <th>Coumarin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>(S)-Nicotine</th>\n",
       "      <td>1.00</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anabasine</th>\n",
       "      <td>0.68</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Atropine</th>\n",
       "      <td>0.40</td>\n",
       "      <td>0.35</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cytisine</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.36</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Echimidine</th>\n",
       "      <td>0.18</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.14</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Scopolamine</th>\n",
       "      <td>0.39</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.38</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Caffeine</th>\n",
       "      <td>0.28</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.20</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coumarin</th>\n",
       "      <td>0.27</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.32</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              (S)-Nicotine  Anabasine  Atropine  Cytisine  Echimidine  \\\n",
       "(S)-Nicotine          1.00       0.68      0.40      0.37        0.18   \n",
       "Anabasine             0.68       1.00      0.35      0.44        0.11   \n",
       "Atropine              0.40       0.35      1.00      0.36        0.36   \n",
       "Cytisine              0.37       0.44      0.36      1.00        0.14   \n",
       "Echimidine            0.18       0.11      0.36      0.14        1.00   \n",
       "Scopolamine           0.39       0.32      0.88      0.35        0.38   \n",
       "Caffeine              0.28       0.27      0.21      0.33        0.09   \n",
       "Coumarin              0.27       0.26      0.30      0.38        0.02   \n",
       "\n",
       "              Scopolamine  Caffeine  Coumarin  \n",
       "(S)-Nicotine         0.39      0.28      0.27  \n",
       "Anabasine            0.32      0.27      0.26  \n",
       "Atropine             0.88      0.21      0.30  \n",
       "Cytisine             0.35      0.33      0.38  \n",
       "Echimidine           0.38      0.09      0.02  \n",
       "Scopolamine          1.00      0.20      0.29  \n",
       "Caffeine             0.20      1.00      0.32  \n",
       "Coumarin             0.29      0.32      1.00  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# calculate similarity matrices, as a data frame\n",
    "SimilaritiesDice2 = pd.DataFrame(\n",
    "    np.array([[round(DataStructs.DiceSimilarity(a,b),2) for b in Morgan2FP] for a in Morgan2FP]),\n",
    "    columns=mols.index, index = mols.index)\n",
    "# look at the results\n",
    "SimilaritiesDice2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5f605945-e63a-4beb-a328-eb234b223cf2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# hierarchical clustering and heatmap\n",
    "sns.clustermap(SimilaritiesDice2,annot=True, linewidths=.5, cmap=\"flare\")\n",
    "plt.title(\"Morgan 2, Dice\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b0e8b0e7-07cc-438f-9aa7-c00217e326ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "#\n",
    "# a simple sub for creation and visualisation of a similarity network\n",
    "#\n",
    "def similarityNetwork(**kwargs):\n",
    "    #\n",
    "    # Usage::\n",
    "    #\n",
    "    # similarityNetwork(simMat=<data frame>, thresh=<float>[, notebook =<boolean>][,html=<filename>])\n",
    "    #\n",
    "    simMat = kwargs.get('simMat') # data frame containing the similarity matrix\n",
    "    thresh = kwargs.get('thresh') # similarity threshod\n",
    "    networkName = kwargs.get('plotTitle','similarity')\n",
    "    noteBookFlag = kwargs.get('notebook', True) # visualize in notebook or new boweser window?\n",
    "    htmlFile = kwargs.get('html', 'test.html')  # \n",
    "    if not isinstance(noteBookFlag, (bool)):\n",
    "        noteBookFlag = True\n",
    "            \n",
    "    # select a similarity matrix and a threshold\n",
    "    #simMat = ECFP2SimilaritiesDice\n",
    "    #thresh = 0.4\n",
    "    scale = 1.0\n",
    "\n",
    "    from pyvis.network import Network\n",
    "    \n",
    "    titleStr = str(networkName)+\"; threshold=\"+str(thresh)\n",
    "    \n",
    "    net = Network(notebook=noteBookFlag,height='1000px', width='100%',heading=titleStr)\n",
    "\n",
    "    # set network display options\n",
    "    if noteBookFlag:\n",
    "        net.set_options('''\n",
    "        var options = {\n",
    "          \"nodes\": {\n",
    "            \"font\": {\n",
    "              \"size\": 22\n",
    "            },\n",
    "            \"shape\": \"text\",\n",
    "            \"shapeProperties\": {\n",
    "              \"borderRadius\": 7,\n",
    "              \"useImageSize\": true\n",
    "            }\n",
    "          },\n",
    "          \"edges\": {\n",
    "            \"color\": {\n",
    "              \"inherit\": true\n",
    "            },\n",
    "            \"font\": {\n",
    "              \"size\": 22\n",
    "            },\n",
    "            \"smooth\": false\n",
    "          },\n",
    "          \"physics\": {\n",
    "            \"barnesHut\": {\n",
    "              \"gravitationalConstant\": -10400,\n",
    "              \"centralGravity\": 0,\n",
    "              \"springLength\": 145,\n",
    "              \"springConstant\": 0.05,\n",
    "              \"damping\": 0.09,\n",
    "              \"avoidOverlap\": 0.41\n",
    "            },\n",
    "            \"minVelocity\": 0.75\n",
    "          }\n",
    "        }\n",
    "        ''')\n",
    "\n",
    "    # add nodes (aka molecules)\n",
    "    for m in mols.index:\n",
    "        net.add_node(m,\n",
    "                     label=m)#,color='rgba(0,0.9,0.9,1)')#,image=molImages[0][m])\n",
    "\n",
    "    scale = 1.0\n",
    "\n",
    "    # create edges (aka pairwise similarities),\n",
    "    # for all connections with a weight( aka similarity) exceeding.d the threshold\n",
    "    for (i,j) in combinations(simMat.index,2):\n",
    "        \n",
    "        if simMat[i][j] > thresh:\n",
    "            labStr = str(round(100*simMat[i][j]))+\"%\" # just a string like \"72%\"\n",
    "            simStr = str(round(simMat[i][j],2))       # just a string like \"0.72\"\n",
    "            net.add_edge(i,j, \n",
    "                         weight=simMat[i][j], \n",
    "                         value=simMat[i][j]*scale, \n",
    "                         label=labStr,\n",
    "                         font='arial',\n",
    "                         size=36)#,\n",
    "                         #color='rgba(1,0.5,0,'+simStr+')') #title=simMat[i][j])\n",
    "            # for more options see: https://visjs.github.io/vis-network/docs/network/edges.html\n",
    "\n",
    "    # actual network properties\n",
    "    #net.enable_physics(True)\n",
    "    if not noteBookFlag:\n",
    "        net.show_buttons() \n",
    "    # net.set_options('var options = {\"physics\": {\"hierarchicalRepulsion\": { \"centralGravity\": 0,\"nodeDistance\": 170},    \"minVelocity\": 0.75,   \"solver\": \"hierarchicalRepulsion\"  }}')\n",
    "    return net.show(htmlFile)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "10919ee2-f26a-474c-affe-b5ffd9e7a585",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"1000px\"\n",
       "            src=\"Alkaloids_Similarity_Graph.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x23eba510250>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "similarityNetwork(simMat=SimilaritiesDice2, thresh=0.30, html=\"Alkaloids_Similarity_Graph.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ad7b3522-4ccf-47af-b16b-a53c84669170",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9a10851e-7490-4be0-a74b-c6ce2b3417f7",
   "metadata": {},
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